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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

AFRL Additive Manufacturing Modeling Series: Challenge 4, In Situ Mechanical Test of an IN625 Sample with Concurrent High-Energy Diffraction Microscopy Characterization

In this work, we describe 3D characterization of an additively manufactured Inconel 625 nickel-base superalloy specimen conducted during a uniaxial tension test using a suite of nondestructive x-ray techniques. High-energy diffraction microscopy in both near- and far-field modalities are employed in situ to track evolution of the material orientation and stress–strain fields at six points during the mechanical test, and these data streams are registered with micro-computed tomography reconstructions which probe the material density. This data volume was matched to a multi-modal serial sectioning characterization of the specimen taken after loading, described in this article’s companion. Twenty-eight grains which were monitored throughout the experiment were selected to form the basis for AFRL AM Modeling Series Challenge 4, Microscale Structure-to-Properties.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Residual stress accumulation in large-scale Ti-6Al-4V wire-arc additive manufacturing

Large-scale additive manufacturing (AM) is of interest in the manufacturing industry to produce components of dimensions on the order of hundreds of millimeters to meters in scale. Wire-arc AM (WAAM) of Ti-6Al-4V (Ti64) is an attractive technique for large-scale AM in the aerospace industry, give the high strength-to-weight ratio of the material and high deposition rate of the process. However, due to the large scale, significant distortion and residual stresses are developed in the material during deposition and cooling, potentially leading to part failure. WAAM of a prototypical large-scale Ti64 machine tool component is studied in this work via finite element analysis (FEA). Element activation/deactivation technique is employed to simulate deposition and the resulting distortion and residual stress (RS) predictions are analyzed to evaluate the possibility of crack formation. Significant distortion (∼10 mm) and RS (>1300 MPa) is predicted, suggesting the formation of cracks and possible crack propagation into the build region. Incorporation of fillets significantly reduces RS concentration regions, thus reducing the possibility of part failure. Material deposition sequence also affects the RS pattern in the build.

Mathews, Ritin↗
DOE OSTI2020

Real-Time Defect Correction in Large-Scale Polymer Additive Manufacturing via Thermal Imaging and Laser Profilometer

Defects can result in a failed part and are costly in terms of time and material. This cost is even greater in the context of large-scale additive manufacturing where the objects can be very large. As a result, a great deal of research has focused on defect identification and mitigation. To address defects during object construction, researchers at Oak Ridge National Laboratory’s Manufacturing Demonstration Facility investigated an in-situ control system comprised of two sensors: a thermal camera and laser profilometer. This control system adjusted material flow and build speed to mitigate three types of defects: low layer times, underfill, and overfill. Several test objects were constructed. The control system was found to adjust build parameters to handle low layer times of approximately 15 seconds and height deviations from -100% underfill (the absence of a layer) to 50% overfill. Within two layers, height deviations could be returned to within 10% of the expected layer height. Further, preliminary results suggest the system can compensate for uneven build surfaces.

Borish, Michael↗
DOE OSTI2023

A fully coupled thermal–microstructural–mechanical finite element process model for directed energy deposition additive manufacturing of Ti–6Al–4V

A fully coupled thermal–microstructural–mechanical finite element modelling framework is developed to investigate the distortion and residual stresses during directed energy deposition (DED) of multi-phase Ti–6Al–4V alloy. The Johnson–Cook constitutive model is used to predict the yield strength of each phase as a function of strain, strain rate and temperature where the flow stress is calculated by a linear mixing rule based on the volumetric phase fractions. A thin-walled rectangular sample is chosen as the reference geometry and the results are compared with experimentally measured in situ thermal history and distortion data, where a reasonable agreement is achieved. The proposed modelling framework with physics-based material constitutive model provides useful information for a better understanding of process–microstructure–property relations in additive manufacturing by DED.

Tunay, Merve↗
DOE OSTI2020

Imaging of Calibrated Defects in Additively Manufactured Materials: Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components

Additive manufacturing (AM, or 3D printing) for commercial nuclear energy applications is an emerging method for cost-efficient manufacturing aimed at replacing aging nuclear reactor parts and reducing costs for new construction. Known material flaws in AM include low-density regions consisting of non-sintered powder, which have to be detected to ensure the safety of long-term performance nuclear reactor components. Currently, limited options are available for nondestructive evaluation (NDE), either during or post manufacturing. As a solution to NDE of AM, we are developing pulsed thermal imaging which is non-contact, one-sided, and scalable to arbitrary size and shape of the AM parts. Pulsed thermography (PT) system utilizes a high intensity flash lamp to rapidly heat surface of sample, and a high sensitivity fast-frame megapixel infrared (IR) camera to capture data of surface temperature variations. The acquired data cube consists of a stack of surface temperature images taken at different times. Information about material internal defects is extracted by analyzing the data cube. This report provides results of preliminary performance evaluation of pulsed thermal imaging capability in detection of imprinted flaws in AM metallic structures. The flaws were introduced into AM parts as imprinted hemispherical low density regions, consisting of trapped un-sintered metallic powder. Specimens for developed for this study consisted of AM stainless steel 316 and Inconel 718 plates. The diameters of imprinted defects varied from 1mm to 8mm, and their depths below the plate flat surface varied between 1mm and 6mm. Pulsed thermal tomography (PTT) processes the measured data cube to obtain 3D reconstructions of material effusivity using a unique inversion algorithm developed at Argonne. PTT has been previously used in imaging of similar size flat bottom hole (FBH) simulated defects in stainless steel 316 and Inconel 718 specimens. In the study involving AM specimens, PTT imaging results have shown that 1mm-diameter defects located 1mm and 2mm below the surface of specimens were detectable. Larger size defects were detectable at greater depth. We also explored an alternative approach to detection of material flaws in PT data cube, which is using neural learning-based approach to blind source separation. Detection of small material defects requires finding features in the data cube which have signal contrast levels approaching sensitivity limit of IR camera. In this study, an optimized Neural Learning based Blind Source Separation (NLBSS) algorithm, including Principal Component Analysis (PCA), and Independent Component Analysis (ICA) is demonstrated to automatically extract principal temporal and spatial features of thermography frames to enhance flaw detection. By using the NLBSS algorithm, material internal defects can be automatically detected. Furthermore, this processing approach compensates for experimental thermal imaging artifacts, such as noise and uneven heating. By merging artificial intelligence with phtotothermics, the NDE system detects internal calibrated defects of various sizes and depths in AM nuclear-grade metallic alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Microstructure Alignment Effects from Engineered Cooling during Additive Manufacturing of Alnico Magnets from Prealloyed Powder

Alnico is a rare-earth free; permanent magnet (PM) which maintains its saturation magnetization while at temperatures up to 550°C but lacks the coercivity and energy product needed for a wide range of demanding applications. With an optimal set of processing and manufacturing techniques, Alnico could replace Dy-free Nd-Fe-B magnets in certain applications if the microstructure is textured in a $\langle$001$\rangle$ direction. Additive manufacturing (AM) of near-net-shape magnets may provide such texture. To investigate the possibility, directed-energy deposition (DED) in conjunction with an actively cooled substrate was used to build samples with a compositionally modified, gas-atomized, Alnico 8 alloy. The resulting samples were solutionized and quenched, followed by magnetic annealing and a heat treatment. Magnetic properties and microstructures are compared to previous work.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

NASA's Approach to Additive Manufacturing Certification: Methodologies for Qualification of Additively Manufactured Aerospace Hardware

The implementation of additive manufacturing techniques to produce critical spaceflight systems is well underway. These technologies will be a key contributor to developing both launch vehicles and spacecraft that will play a crucial role in delivering the first woman and first person of color to the surface of the moon in 2025. To assist in the assurance of flight readiness, NASA has created comprehensive certification based standards for mature technologies for both metallic and nonmetallic materials.

Alison Park↗